///

```Python hl_lines="8"
{!> ../../docs_src/header_param_models/tutorial002_py310.py!}
```

////

//// tab | Python 3.9+ non-Annotated

/// tip | Dica

Utilize a versão com `Annotated` se possível.

///

```Python hl_lines="10"
{!> ../../docs_src/header_param_models/tutorial002_py39.py!}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip | Dica

First, you need to import `BaseModel` from `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Create your data model

Then you declare your data model as a class that inherits from `BaseModel`.

Use standard Python types for all the attributes:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

Let's say you have a Pydantic model with default values, like this one:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:7] hl[7] *}

### Model for Input

If you use this model as an input like here:

{* ../../docs_src/separate_openapi_schemas/tutorial001_py310.py ln[1:15] hl[14] *}

...then the `description` field will **not be required**. Because it has a default value of `None`.

//// tab | Python 3.10+

```Python hl_lines="7"
{!> ../../docs_src/separate_openapi_schemas/tutorial001_py310.py[ln:1-7]!}

# Code below omitted 👇
```

<details>
<summary>👀 Visualização completa do arquivo</summary>

```Python
{!> ../../docs_src/separate_openapi_schemas/tutorial001_py310.py!}
```

</details>

////

//// tab | Python 3.9+

```Python hl_lines="9"

"docs_src/security/tutorial004_an_py39.py" = ["B904"]
"docs_src/security/tutorial004_py310.py" = ["B904"]
"docs_src/security/tutorial005.py" = ["B904"]
"docs_src/security/tutorial005_an.py" = ["B904"]
"docs_src/security/tutorial005_an_py310.py" = ["B904"]
"docs_src/security/tutorial005_an_py39.py" = ["B904"]
"docs_src/security/tutorial005_py310.py" = ["B904"]
"docs_src/security/tutorial005_py39.py" = ["B904"]

This also means that in Python 3.10, you can use `Something | None`:

//// tab | Python 3.10+

```Python hl_lines="1"
{!> ../../docs_src/python_types/tutorial009_py310.py!}
```

////

//// tab | Python 3.8+

```Python hl_lines="1  4"
{!> ../../docs_src/python_types/tutorial009.py!}
```

////

//// tab | Python 3.8+ alternative

////

//// tab | Python 3.10+ non-Annotated

/// tip

Prefer to use the `Annotated` version if possible.

///

```Python hl_lines="7  48  55-56  59-60  69-75"
{!> ../../docs_src/security/tutorial004_py310.py!}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip

Prefer to use the `Annotated` version if possible.

///

```Python hl_lines="8  49  56-57  60-61  70-76"

```

////

//// tab | Python 3.10+ non-Annotated

/// tip | Dica

Prefira usar a versão `Annotated`, se possível.

///

```Python hl_lines="2  74"
{!> ../../docs_src/security/tutorial003_py310.py!}
```

////

//// tab | Python 3.8+ non-Annotated

/// tip | Dica

Prefira usar a versão `Annotated`, se possível.

///

```Python hl_lines="4  76"

You can use `jsonable_encoder` for that.

It receives an object, like a Pydantic model, and returns a JSON compatible version:

{* ../../docs_src/encoder/tutorial001_py310.py hl[4,21] *}

In this example, it would convert the Pydantic model to a `dict`, and the `datetime` to a `str`.